CN108648131A - A kind of hidden image restoration methods based on multi-direction window - Google Patents
A kind of hidden image restoration methods based on multi-direction window Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G06T1/0021—Image watermarking
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- G06T2201/00—General purpose image data processing
- G06T2201/005—Image watermarking
- G06T2201/0065—Extraction of an embedded watermark; Reliable detection
Abstract
The invention discloses a kind of hidden image restoration methods based on multi-direction window, characterized in that includes the following steps：1）Determine direction window；2）Determine direction window pixel valuation；3）Using multi-direction window restoration image；4）Repair the complete recovery that isolated point completes entire hidden image.This method has the characteristics that directionality, the hidden image of recovery have preferable visual effect using image local area.
Description
Technical field
The present invention relates to Information hiding and image processing field, specifically a kind of hidden image based on multi-direction window is extensive
Compound method.
Background technology
With popularizing for the development of computer network, E-Government and e-commerce, in the big data epoch to the peace of information
Full storage, transmission and access etc. propose new challenge.Although digital information brings facility, in a network
The information of transmission is easy to be trapped, and the data of storage can be attacked, if important information is stolen or distorts, therefore user may be
And it sustains a great loss.
Information hiding is also referred to as image watermarking, is that the secret informations such as image, chart, data, sound are hidden in image, sound
In the carrier informations such as sound, video.Conceal the containing information of data, it is difficult to the difference being therefore easily perceived by humans out before and after Information hiding,
Only validated user just can correctly extract secret information from containing information.Due to being embedded in front and back carrier no significant difference,
Therefore the use that operation has no effect on original vector is hidden.Information Hiding Techniques, can extensive use as a kind of information protecting method
In medium copyright protection, secret communication, secret protection, national defense and military etc., Information Hiding Techniques preferably resolve information
Security fields problems are an important research hot spots in current information security field.
For Information hiding mainly using image as carrier, the information if necessary to protection is also image, then can be by a width figure
Safeguard protection is realized as being hidden among another piece image.Since digital picture has the characteristics that be easy to modification, is storing and passing
It in defeated process, carries close image and is subject to the attacks such as noise jamming, the hidden image extracted in this way similarly can be by
Destruction to a certain extent, if carrying out denoising to carrying close image, though existing image de-noising method can effectively remove carry it is close
The noise of image, but the pixel bit for carrying and being hidden in close image is also destroyed simultaneously, cause from the close image of load after recovery
The hidden image extracted is ineffective, since the part position of pixel in hidden image is destroyed, so hidden image is by not
The random noise disturbance of rule, it is ideal not to the utmost with existing image recovery method effect.
Invention content
The purpose of the present invention is in view of the deficiencies of the prior art, and it is extensive to provide a kind of hidden image based on multi-direction window
Compound method.This method has the characteristics that directionality, the hidden image of recovery have preferable vision using image local area
Effect.
Realizing the technical solution of the object of the invention is：
A kind of hidden image restoration methods based on multi-direction window include the following steps unlike the prior art：
1) direction window is determined：If carrier and hiding information are all images, when the close image of load is in the process transmitted or stored
Middle, when extracting hidden image, certain positions in hidden image to be caused to be destroyed by noise jamming, detection carries making an uproar for close image
Sound point, determines the position being destroyed in hidden image pixel, with h to pixel p (x, y) is destroyed in hidden image position into rower
Note, if kth (1≤k≤8) position of pixel p (x, y) is destroyed, h (k)=1 indicates that the pixel position is incredible；If pixel
The kth position of point p (x, y) is not destroyed, then h (k)=0, indicates that the pixel position is believable, since the texture edge of image has
There is certain directionality, by restoring image with directive filter window, the recovery effects of image can be improved, with pixel
Centered on point, by increasing separately one group of pixel, the side in 4 directions of formation on vertical, horizontal, 45 degree and 135 degree of 4 directions
To window Di(i=1,2,3,4), i.e. D1、D2、D3And D4Respectively the vertical, horizontal of pixel p, 45 degree and 135 degree of 4 Directional Windows
Mouthful, the pixel in application direction window is treated repairing pixel and is repaired, and recovery value in this direction can be obtained, in conjunction with 4
The repair data in direction determines the final reparation result of the pixel；
2) direction window pixel valuation is determined：If p (x, y) is pixel to be repaired, in the direction window D of p (x, y)i(i=
1,2,3,4) high 5 all believable pixels are q (x inj i,yj i) (i=1,2,3,4；J=1,2 ..., ti), wherein q (xj i,yj i)
For j-th of pixel of i-th of window, tiFor high 5 all believable number of pixels, h in i-th of windowj i(k) (1≤k≤8) are
Pixel q (xj i,yj i) kth position mark value, enable：
Wherein rj iFor pixel confidence level, n is positive integer,
Since neighborhood territory pixel is closer with pixel to be repaired, correlation is bigger, and pixel value is more possible to close to be repaired
Multiple pixel value, if dj iFor neighborhood territory pixel q (xj i,yj i) with the Euclidean distance of pixel p (x, y) to be repaired, then：
It enables：
Then wj iFor neighborhood territory pixel point q (xj i,yj i) apart from weights,
The pixel estimated value A to be repaired of i-th of windowiIt calculates as follows：
Obtain 4 direction window estimated value A of p points1, A2, A3, A4；
3) multi-direction window restoration image is applied:4 direction window D are obtained according to step 2)iEstimated value Ai(i=1,2,
3,4) D, is adjustediIn each pixel insincere position, make the value and A of each pixel in windowiAbsolute value of the difference is minimum, obtains everywhere
Manage rear hatch DiIn pixel value be Mi,j(i=1,2,3,4；J=1,2 ..., ti),For direction DiThe mean value of middle pixel, Ei
For direction window DiThe variance of middle pixel, then：
It enables：
Ez=min (E1,E2,E3,E4)
Then AzFor the optimal estimation value of pixel p to be repaired, the insincere position of pixel p to be repaired is adjusted, pixel p to be repaired is made
Value ApWith AzAbsolute value of the difference is minimum, and the recovery value of pixel p can be obtained, and realizes the recovery to hidden image；
4) isolated point is repaired：All pixels after step 3) in hidden image are all resumed, if restoring pixel and neighbour
There is larger differences for domain pixel, then the pixel may be an isolated point, need to handle the pixel, if the 3 of p
× 3 neighborhood territory pixel is q (i) (0<I≤8), recovery value AiIfWherein T1For threshold value, enable：
ThenFor the estimated value of pixel p, the insincere position of pixel to be repaired is adjusted, recovery value A can be obtainedp, complete whole
The complete recovery of a hidden image, the step remove isolated point in image, improve the quality of hidden image.
This technical solution determines that hidden image is destroyed insincere position in pixel, that is, needs the position repaired first, calculates
The estimated value of 4 direction windows of pixel to be repaired, the pixel of each direction window is determined according to the estimated value of 4 direction windows
Variance, the corresponding estimated value of window of pixel variance minimum are optimal estimation value, adjust the insincere position of pixel to be repaired, and most
The excellent immediate pixel value of estimated value is pixel recovery value, to restore hidden image, when carrying close image by noise jamming, is led to
The hidden image for crossing the technical program recovery has preferable visual effect.
This method has the characteristics that directionality, the hidden image of recovery have preferable vision using image local area
Effect.
Description of the drawings
Fig. 1 is the hidden image in embodiment；
Fig. 2 is the carrier image in embodiment；
Fig. 3 is that Fig. 1 is hidden to the close image of load obtained in the picture using LSB hidden algorithms in embodiment；
Fig. 4 is to apply the obtained destruction image of salt-pepper noise that probability is 0.1 to Fig. 3 in embodiment, figure intermediate value be 0 or
255 pixel is salt-pepper noise；
Fig. 5 is the hidden image extracted from Fig. 4 in embodiment, and the gray pixels in figure are that pixel to be repaired has been destroyed,
Original value is 161, extraction of values 177；
Fig. 6-1 is pixel vertical direction D to be repaired in embodiment1The high 5 believable pixel maps of direction window；
Fig. 6-2 is pixel level direction D to be repaired in embodiment2The high 5 believable pixel maps of direction window；
Fig. 6-3 is 45 degree of direction D of pixel to be repaired in embodiment3The high 5 believable pixel maps of direction window；
Fig. 6-4 is 135 degree of direction D of pixel to be repaired in embodiment4The high 5 believable pixel maps of direction window；
Fig. 7-1 is pixel vertical direction D to be repaired in embodiment1The high 5 trustworthy pixels confidence level figure of direction window；
Fig. 7-2 is pixel level direction D to be repaired in embodiment2The high 5 trustworthy pixels confidence level figure of direction window；
Fig. 7-3 is 45 degree of direction D of pixel to be repaired in embodiment3The high 5 trustworthy pixels confidence level figure of direction window；
Fig. 7-4 is 135 degree of direction D of pixel to be repaired in embodiment4The high 5 trustworthy pixels confidence level figure of direction window；
Fig. 8-1 is pixel vertical direction D to be repaired in embodiment1The high 5 trustworthy pixels distance weighting figure of direction window；
Fig. 8-2 is pixel level direction D to be repaired in embodiment2The high 5 trustworthy pixels distance weighting figure of direction window；
Fig. 8-3 is 45 degree of direction D of pixel to be repaired in embodiment3The high 5 trustworthy pixels distance weighting figure of direction window；
Fig. 8-4 is 135 degree of direction D of pixel to be repaired in embodiment4The high 5 trustworthy pixels distance weighting figure of direction window；
Fig. 9-1 is the vertical direction D of pixel p1Template window figure；
Fig. 9-2 is the template window figure of the horizontal direction D2 of pixel p；
Fig. 9-3 is the template window figure of 45 degree of direction D3 of pixel p；
Fig. 9-4 is the template window figure of 135 degree of direction D4 of pixel p.
Specific implementation mode
The content of present invention is described in further detail with reference to the accompanying drawings and examples, but is not the limit to the present invention
It is fixed.
Embodiment：
A kind of hidden image restoration methods based on multi-direction window, include the following steps：
1) direction window is determined：If carrier and hiding information are all images, hidden image as shown in Figure 1, carrier image such as
Shown in Fig. 2, when carrying close image as shown in Figure 3 during transmission or storage by noise jamming, as shown in figure 4, hidden extracting
When Tibetan image is as shown in Figure 5, certain positions in hidden image can be caused to be destroyed, detection carries the noise spot of close image, determines hidden
The position being destroyed in image pixel is hidden, the position that pixel p (x, y) is destroyed in hidden image is marked with h, if pixel p (x,
Y) kth (1≤k≤8) position is destroyed, then h (k)=1, indicates that the pixel position is incredible；If the kth of pixel p (x, y)
Position is not destroyed, then h (k)=0, indicates that the pixel position is believable, since the texture edge of image has certain direction
Property, by restoring image with directive filter window, the recovery effects of image can be improved, centered on pixel, lead to
It crosses on vertical, horizontal, 45 degree and 135 degree of 4 directions and increases separately one group of pixel, form the direction window D in 4 directionsi(i
=1,2,3,4), i.e. D1、D2、D3And D4Respectively the vertical, horizontal of pixel p, 45 degree and 135 degree of 4 direction windows, such as Fig. 9-1
To shown in Fig. 9-4；
2) direction window pixel valuation is determined：If p (x, y) is pixel to be repaired, in the direction window D of p (x, y)i(i=
1,2,3,4) high 5 all believable pixels are q (x inj i,yj i) (i=1,2,3,4；J=1,2 ..., ti), such as Fig. 6-1 to Fig. 6-
Shown in 4, wherein q (xj i,yj i) be i-th of window j-th of pixel, tiFor high 5 all believable pixels in i-th of window
Number, hj i(k) (1≤k≤8) are pixel q (xj i,yj i) kth position mark value, enable：
Wherein rj iFor pixel confidence level, as shown in Fig. 7-1 to Fig. 7-4, n is positive integer,
Since neighborhood territory pixel is closer with pixel to be repaired, correlation is bigger, and pixel value is more possible to close to be repaired
Multiple pixel value, if dj iFor neighborhood territory pixel q (xj i,yj i) with the Euclidean distance of pixel p (x, y) to be repaired, then：
It enables：
Then wj iFor neighborhood territory pixel point q (xj i,yj i) apart from weights, as shown in Fig. 8-1 to Fig. 8-4,
The pixel estimated value A to be repaired of i-th of windowiIt calculates as follows：
Obtain 4 direction window estimated value A of p points1=144, A2=161, A3=161, A4=161；
3) multi-direction window restoration image is applied:4 direction window D are obtained according to step 2)iEstimated value Ai(i=1,2,
3,4) D, is adjustediIn each pixel insincere position, make the value and A of each pixel in windowiAbsolute value of the difference is minimum, obtains everywhere
Manage rear hatch DiIn pixel value be Mi,j(i=1,2,3,4；J=1,2 ..., ti),For direction DiThe mean value of middle pixel, Ei
For direction window DiThe variance of middle pixel, then：
Obtain E1=35.25, E2=6.12, E3=8.63, E3=7.65, then Ez=min (E1,E2,E3,E4)=E2.Thus
Understand A2=161 be the optimal estimation value of pixel to be repaired, adjusts all insincere positions of pixel 177 to be restored, it is extensive to obtain pixel
Complex value is 161；
4) isolated point is repaired：All pixels after step 3) in hidden image are all resumed, if restoring pixel and neighbour
There is larger differences for domain pixel, then the pixel may be an isolated point, need to handle the pixel, if the 3 of p
× 3 neighborhood territory pixel is q (i) (0<I≤8), recovery value AiIfWherein T1For threshold value, enable:
ThenFor the estimated value of pixel p, the insincere position of pixel to be repaired is adjusted, recovery value A can be obtainedp, complete whole
The step for complete recovery of a hidden image, this example, removes isolated point in image, improves the quality of hidden image.
Claims (1)
1. a kind of hidden image restoration methods based on multi-direction window, characterized in that include the following steps：
1) direction window is determined：If carrier and hiding information are all images, when close image quilt during transmission or storage of load
Noise jamming can cause certain positions in hidden image to be destroyed when extracting hidden image, and detection carries the noise of close image
Point determines the position being destroyed in hidden image pixel, and the position that pixel p (x, y) is destroyed in hidden image is marked with h,
If kth (1≤k≤8) position of pixel p (x, y) is destroyed, h (k)=1 indicates that the pixel position is incredible；If pixel p
The kth position of (x, y) is not destroyed, then h (k)=0, indicates that the pixel position is believable, centered on pixel, by perpendicular
Directly, one group of pixel is increased separately on level, 45 degree and 135 degree of 4 directions, forms the direction window D in 4 directionsi(i=1,2,
3,4), i.e. D1、D2、D3And D4Respectively the vertical, horizontal of pixel p, 45 degree and 135 degree of 4 direction windows；
2) direction window pixel valuation is determined：If p (x, y) is pixel to be repaired, in the direction window D of p (x, y)i(i=1,2,3,
4) high 5 all believable pixels are q (x inj i,yj i) (i=1,2,3,4；J=1,2 ..., ti), wherein q (xj i,yj i) it is i-th
J-th of pixel of a window, tiFor high 5 all believable number of pixels, h in i-th of windowj i(k) (1≤k≤8) are pixel q
(xj i,yj i) kth position mark value, enable：
Wherein rj iFor pixel confidence level, n is positive integer,
Since neighborhood territory pixel is closer with pixel to be repaired, correlation is bigger, and pixel value is more possible to close to double image to be repaired
Element value, if dj iFor neighborhood territory pixel q (xj i,yj i) with the Euclidean distance of pixel p (x, y) to be repaired, then：
It enables：
Then wj iFor neighborhood territory pixel point q (xj i,yj i) apart from weights,
The pixel estimated value A to be repaired of i-th of windowiIt calculates as follows：
Obtain 4 direction window estimated value A of p points1, A2, A3, A4；
3) multi-direction window restoration image is applied:4 direction window D are obtained according to step 2)iEstimated value Ai(i=1,2,3,
4) D, is adjustediIn each pixel insincere position, make the value and A of each pixel in windowiAbsolute value of the difference is minimum, is handled
Rear hatch DiIn pixel value be Mi,j(i=1,2,3,4；J=1,2 ..., ti),For direction DiThe mean value of middle pixel, EiFor
Direction window DiThe variance of middle pixel, then：
It enables：
Ez=min (E1,E2,E3,E4)
Then AzFor the optimal estimation value of pixel p to be repaired, the insincere position of pixel p to be repaired is adjusted, the value of pixel p to be repaired is made
ApWith AzAbsolute value of the difference is minimum, and the recovery value of pixel p can be obtained, and realizes the recovery to hidden image；
4) isolated point is repaired：All pixels after step 3) in hidden image are all resumed, if restoring pixel and neighborhood picture
There is larger differences for element, then the pixel may be an isolated point, if 3 × 3 neighborhood territory pixel of p is q (i) (0<i≤
8), recovery value AiIfWherein T1For threshold value, enable：
ThenFor the estimated value of pixel p, the insincere position of pixel to be repaired is adjusted, recovery value A can be obtainedp, complete entire hidden
Hide the complete recovery of image.
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